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Interior point methods for placement
1994 IEEE International Symposium on Circuits and Systems (ISCAS), 1994In VLSI layout optimization, the placement problem is usually solved with simulated annealing or heuristic algorithms. These procedures often begin with random initial configurations but may benefit greatly (in terms of execution time or quality of solution) when good initial relative placements are provided.
P. Chin, Anthony Vannelli
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On the Complexity of a Practical Interior-Point Method
SIAM Journal on Optimization, 1998Summary: The theory of self-concordance in convex optimization has been used to analyze the complexity of interior-point methods based on Newton's method. For large problems, it may be impractical to use Newton's method; here we analyze a truncated-Newton method, in which an approximation to the Newton search direction is used.
Stephen G. Nash, Ariela Sofer
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1996
It was mentioned earlier that the standard simplex method searches for an optimum to a linear program by moving along the surface of a convex polyhedron from one extreme point to an adjacent extreme point in a fashion such that the objective value is nondecreasing between successive basic feasible solutions.
Cornelis Roos, Jean-Philippe Vial
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It was mentioned earlier that the standard simplex method searches for an optimum to a linear program by moving along the surface of a convex polyhedron from one extreme point to an adjacent extreme point in a fashion such that the objective value is nondecreasing between successive basic feasible solutions.
Cornelis Roos, Jean-Philippe Vial
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Journal of Optimization Theory and Applications, 1998
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2013
The ellipsoid method has an undeniable historical relevance (due to its role in establishing polynomial time for linear programming with integer data). In addition, its underlying idea is simple and elegant. Unfortunately, it is not efficient in practice compared with both the simplex method and the more recent interior-point methods.
Peter Bürgisser, Felipe Cucker
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The ellipsoid method has an undeniable historical relevance (due to its role in establishing polynomial time for linear programming with integer data). In addition, its underlying idea is simple and elegant. Unfortunately, it is not efficient in practice compared with both the simplex method and the more recent interior-point methods.
Peter Bürgisser, Felipe Cucker
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Barrier Functions in Interior Point Methods
Mathematics of Operations Research, 1996We show that the universal barrier function of a convex cone introduced by Nesterov and Nemirovskii is the logarithm of the characteristic function of the cone. This interpretation demonstrates the invariance of the universal barrier under the automorphism group of the underlying cone.
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The Kantorovich Theorem and interior point methods
Mathematical Programming, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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2008
Linear programs can be viewed in two somewhat complementary ways. They are, in one view, a class of continuous optimization problems each with continuous variables defined on a convex feasible region and with a continuous objective function. They are, therefore, a special case of the general form of problem considered in this text.
David G. Luenberger, Yinyu Ye
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Linear programs can be viewed in two somewhat complementary ways. They are, in one view, a class of continuous optimization problems each with continuous variables defined on a convex feasible region and with a continuous objective function. They are, therefore, a special case of the general form of problem considered in this text.
David G. Luenberger, Yinyu Ye
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Ragnar Frisch and interior-point methods
Optimization Letters, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Olav Bjerkholt, Sjur Didrik Flåm
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The interior-point method for linear programming
IEEE Software, 1992A robust, reliable, and efficient implementation of the primal-dual interior-point method for linear programs, which is based on three well-established optimization algorithms, is presented. The authors discuss the theoretical foundation for interior-point methods which consists of three crucial building blocks: Newton's method for solving nonlinear ...
Greg Astfalk +3 more
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